1. Technical Field
The present invention relates to methods for identifying a currency note using a partial read of the note""s serial number or code. Individual numbers are identified to specific fields in the serial number in order to provide a statistically accurate identification of a note despite an inability to read the entire serial number.
2. Description of Related Art
Optical character recognition (xe2x80x9cOCRxe2x80x9d) is a technology commonly used in the currency processing field for lifting the serial number or code from processed notes. OCR technology is used, for example, for identifying specific notes processed by a high speed currency processing machine, such as those machines manufactured and marketed by Currency Systems International of Irving, Tex., by lifting a note""s serial code using a camera device and then recording the serial code to the note processed.
By way of example, a stack of currency can be fed into the high speed currency processing machine. As one of the functions of the machine, an OCR device reads the serial number or code of notes passed through the machine for processing. These serial numbers can be recorded and identified to specific notes as they are processed. One of the functions of the high speed currency processor may be to sort currency by denomination and stack fit notes for bundling. As the fit notes are stacked, the data processing capabilities of the currency processing machine track the location in the stack of each currency note by serial number. For example, for a processed stack or bundle of one hundred notes in twenty dollar denominations, data is accumulated that will indicate the specific serial number on each note in the stack or bundle and position of each note in the stack.
This information can be particularly useful in a number of potential applications. For example, if this bundle is later distributed by an automatic teller machine (xe2x80x9cATMxe2x80x9d), the ATM can identify the specific notes distributed to a specific account by recording the position of the notes in the stack as they are distributed. The ATM might record that the eighth note in the stack was distributed to a specific account holder on a specific day and time. If later that particular account holder contacts the bank to indicate that the account holder received a counterfeit note, the bank can confirm such claim by requesting that the account holder identify the serial number of the note in question. The bank will be able to tell which note was distributed to the account holder if it knows the position of the note in the bundle and the serial number recorded for the note at that position provided by the high speed currency processing machine. If the serial number provided by the account holder matches the serial number identified to the note distributed, then the bank has confirmed that a counterfeit note was in fact distributed to the account holder.
Another example of a potential application of OCR technology is to assist in the identity of missing notes. For example, a commercial institution might transfer bundles of notes to a central bank in groupings of one hundred notes per bundle. If the central bank determines that there are only ninety-nine notes in a bundle that should have contained one hundred, it is extremely useful to be able to identify the serial number of the ninety-nine notes that were received and compare that data with the serial numbers recorded by the commercial institution to the one hundred notes that it shipped. By identifying the serial number of the missing note, it may be possible to identify the location of the note in the bundle and determine if there had been a problem at some stage of note processing.
Another example of a potential use of OCR technology involves notes deposited from a till when the till depositor later claims that the depositee did not properly credit all the notes deposited. If the till depositor can identify the serial numbers of each note deposited, the accounting problem might be more easily resolved.
While there are many potentially useful applications incorporating the ability of OCR devices to identify a note""s serial number, unfortunately a consistently accurate read of the entire field of every note""s serial number in a high speed currency processing environment is not feasible given present OCR technology. This difficulty increases with worn or unfit notes. Consequently, it is not uncommon for OCR devices to obtain only a partial read of a note""s serial number. The fact that extremely worn or soiled notes will always need to be processed along with more fit notes makes it unlikely that any improvement in OCR technology will ever provide the capability of a one hundred percent accuracy rate in reading the entire field of every note processed. Presently, none of the above examples of useful applications of OCR technology can be reliably applied in light of the inability to read the entire serial code of every note processed.
Consequently, a need exists for a method that will accurately identify a note even though the note""s entire serial number could not be obtained by OCR technology. This method should provide positive note identification or negative note discrimination even though only a portion of the OCR is successful. Such a method should be capable of identifying notes through a high level of statistical probability having read only two or more of the identifying fields and should be able to provide some level of discrimination when even only one field is read.
The invention involves methods for identifying a currency note when not all fields of the serial number or code of a note have been read. This is accomplished by recording the position of each field read along with the character identifier found in that field. The method can also combine this information with the position of the note in a specific stack of currency to provide an additional data point.
By way of example, United States currency notes, such as the one illustrated in FIG. 1, generally have serial numbers with ten fields. An OCR lift on a soiled or worn note might only identify one or two characters of the serial number accurately. However, because the field position of each character read on the note can also be identified, the method can determine which fields have been read and then associate the character within each field to the field position. The method then uses this information in order to statistically identify a serial number of a note to the note processed. This information can also be combined with the position of the note in the currency stack. By knowing a small percentage of the characters associated with a specific serial number, the respective field position of each character, and the position of the note in a stack, notes can be identified with a high statistical probability of accuracy. This method, therefore, greatly enhances the usefulness of OCR technology without the necessity of improving on the accuracy of OCR devices.
The above as well as additional features and advantages of the present invention will become apparent in the following written detailed description.